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分段2维主成分分析的超光谱图像波段选择

DOI: 10.11834/jig.20140220

Keywords: 超光谱图像|2维主成分分析|波段选择|波段分组

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Abstract:

目的超光谱图像具有极高的谱间分辨率,巨大的数据量给分类识别等后续处理带来很大压力。为了有效降低图像数据维数,提出基于分段2维主成分分析(2DPCA)的超光谱图像波段选择算法。方法首先根据谱间相关性对原始图像进行波段分组,然后根据主成分反映每个光谱波段的信息比重分别对每组图像进行波段选择,从而实现超光谱图像的谱间降维。结果该算法有效降低了超光谱图像的光谱维数,选择的波段明显反映出不同地物像元矢量的区别。结论实验结果表明,该波段选择算法相对传统算法速度更快,并且较好地保留了原始图像的局部重要信息,对后续处理有积极意义。

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